The continued evolution of semiconductor technologies over the past thirty years have led to low cost, high volume, consumer electronic devices having capabilities and connectivity unprecedented in human history. Today, a teenager armed with a smartphone is able to browse and access content potentially from hundreds of millions of websites and billions of webpages through wireless connectivity to the Internet, exchange messages in electronic, voice, and video remotely or locally, stream high definition video, navigate essentially anywhere in the world through Global Positioning Systems (GPS), and control or obtain data from a range of other local and/or remote electronic devices ranging from activating or deactivating a residential security system to flying a drone.
These same technological advancements have also resulted in many residential homes and office buildings being increasing equipped with network-controllable devices, such as thermostats and lights. Users, through a mobile device such as a smartphone or tablet, can adjust settings of these network-controllable devices from a remote location, using a cloud server program registered on both the mobile and network-controllable devices. Using location services embedded in the mobile device, actions can also be triggered based on the user's location, such as turning on the lights just before a user enters the room. Wi-Fi APs in larger buildings help identify the unique users in each access point location. Most of these homes and buildings are also equipped with security systems which comprise keypads with “stay” and “away”, or equivalently armed/disarmed modes, along with optional infrared, motion, and other sensors for movement detection and audible detection. Such electronic devices as well as those in fields ranging from health, automotive, environmental etc. have led to concepts such as Smart Devices and Networks (SDNs) of which the commonly referred to “Internet of Things” (IoT) forms part.
However, prior art SDN solutions suffer drawbacks including, for example, that the actions where triggered by user location, e.g. based upon acquired GPS location or wireless AP/base station connectivity (presence) and/or triangulation, are typically based on the location of a single PED, e.g. a smartphone. Accordingly, it becomes increasingly difficult to gauge the proper action to take when the SDNs are controlled by more than one user. For example, network-controlled lights within a residence may be programmed to a specific action, e.g. turn off, when the user is not at home, but if said user has guests or other tenants still in the house, the programmed lights will be an inconvenience. Today, the network controllable aspects of the user s residence form one SDN whilst their security system forms another SDN and they are may exploit different network infrastructure and/or common network infrastructure. However, in this scenario it would be evident that connectivity between the SDNs either as a single SDN and/or through Machine-to-Machine (M2M) communications may trigger actions based upon the combined data such that at a basic level the programmed turning off of the lights is linked to the security mode of the residence. In this manner if the user leaves and arms the security system the lights are set to their programmed state but if the user leaves and does not arm the security system then the lights are left unaffected.
Accordingly, there is a requirement for M2M communications between a user's SDNs such as their network-controllable devices and their security system, wherein the combined knowledge of these multiple SDNs is employed to trigger actions for one or more SDNs based upon the combined states of all the SDNs.
Other aspects and features of the present invention will become apparent to those ordinarily skilled in the art upon review of the following description of specific embodiments of the invention in conjunction with the accompanying figures.